Data Scientist 3

at  Lam Research

REQUIREMENT OF QUALIFICATION

• Minimum 5 to 7 years of proven continuous improvement analytical experience from a similar role, including project management and business analysis.
• BS degree in engineering, quality management, computer science, related/applicable science, or master’s degree.
• Semiconductor industry experience.
• Exceptional knowledge and history of implementation of AI to solve the most complex challenges of the Lam that lead to efficiency and effectiveness improvements.
• Ability to work on multiple problems simultaneously. Knowledge of Quick base, Power BI capability and development. Ability to present conclusions and recommendations to executive audiences.
• Excellent Knowledge in SQL, Jmp, Python, R, Matlab, or equivalent. Six Sigma certification (Green Belt or higher).
• Advanced expertise in structured problem-solving methodologies (PDCA, DMAIC, 8D) and quality tools.
• Experience in Statistical Process Control (SPC), Gage R&R, Pareto Charts etc. using tools like JMP, Minitab.

Lam Research is looking for a Performance Data Scientist in Lam’s Engineering organization. This is individual will partner with the MFE/TE/IE peers and leaders across the LMM MFE community to identify through the use a common data to effectively prioritize and resolve the Engineering issues in the company impacting our Manufacturing and production customers to meet both short and term business objectives. This role will have a high-profile presence within the organization and will be able to contribute and make a difference in the Engineering performance and culture through knowledge, leadership and influence within the company and ultimately delivering required improvement to our valued customers and internal functions.

• Analyze trends and patterns in Engineering data that drive required Engineering improvement. Strong data analytics skills, statistical knowledge and ability to leverage multiple data sources to enable data-driven insights and effective decision making.
• Strong understanding of database structures and data integration, SQL programming skills, including the use of SQL analytics function, develop reports, dashboards , metric measurement and assessment methods for performance management and predictive modeling.
• Improve data utilization via AI, automation and improve defect determination leading to real time resolution and speeding systemic action.
• Ability to effectively interpret, communicate and articulate details into concise and understandable facts, numbers and actionable items.
• Lead multiple projects simultaneously and demonstrate organizational, prioritization, and time management proficiencies.